Self-Driving Truck Platooning Saves Fuel and Time
The European Union wants to save fuel, reduce accidents and make road transport more sustainable by using convoys that link two to five trucks, using connectivity technology and automated driving support systems to make this a reality.
Over 75% of inland cargo transport within the EU — about 1,750 billion tonne-kilometers (tkm) — travel by road, according to Eurostat. In some European countries, this percentage goes as high as 90% or more.
In comparison, the amount of freight transported by truck in the United States is only 58%.
The EU is funding several initiatives under its Horizon 2020 research and innovation program to reduce fuel consumption and optimize road transport. One such initiative is called the Companion Project.
If 25% of the 1.5 million trucks in Europe engage in platooning — assuming a 5% fuel reduction per vehicle — nearly 1 billion liters (264 million gallons) of fuel per year could be saved, not to mention the corresponding reduction in CO2 emissions, according to the project.
Air drag accounts for up to 25% of a truck’s total fuel consumption. The closer that trucks can drive to each other, the greater the fuel-saving potential. Carbon emissions on a five-truck platoon can be reduced by 10% on the highway when this platooning system is in place.
Since human reaction time is much slower than technology, the only way a tight convey can travel safely is to use advanced self-driving technologies similar to those used in autonomous vehicles. The faster response time of these platooning systems allows a convoy to respond to unexpected situations on the road without endangering the trucks behind the lead truck.
The current technology does require that following truck drivers stay alert and be ready to take control at a split-second’s notice. Maneuvers such as changing lanes or exiting the motorway require each truck in the platoon to drive manually. The leading truck, which is in communication with the infrastructure and all vehicles in the convoy, alerts the drivers behind about when to take the wheel.
To bring truck platooning to the roads, accurate satellite navigation, plus fast and reliable communication between trucks and the infrastructure are required.
DSRC technology provides low-latency and quick response
Several wireless technologies compete in the market, some already available and others still being tested and standardized.
While some countries are waiting for the upcoming 5G networks to enable vehicle-to-vehicle (V2V) and vehicle-to-everything (V2X) communications, the EU has been working with 5GHz WiFi for several years.
The IEEE 802.11p Dedicated Short Range Communications (DSRC) WiFi communication standard provides latency as low as a few milliseconds across two wireless links. DSRC technology is already being designed in by major vehicle manufacturers, including General Motors, Volkswagen and Toyota, 802.11p is now available. Its competitor, the upcoming 5G Release 14 cellular technology — recently just specified by the 3GPP group — will take several years for manufacturers and module makers to implement it in production models.
5G V2X communication technology can be limiting. Using DSRC, however, is a viable solution. For instance, the leading truck can request the road infrastructure to clear the passage of the entire platoon by synchronizing traffic lights and other signaling systems.
The trial results are encouraging
During road tests, the distance between platooning trucks was reduced to 7 meters (23 feet), or 0.3 seconds traveling at 80 kilometers per hour (50 MPH). While the average human response time is around one second, one solution tested — together with the full prototype electronics system behind it — reacts 25 times faster.
While truck platooning adds efficiency to road transport, rail transport is far more efficient and the EU is working on making a bigger shift in that direction. In the meantime, electric trucks are also on the horizon.
Originally published as “EU Bets Truck Platooning Could Result in Huge Fuel Savings” on TU-Automotive
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